Wi-Fi Walkman A wireless handhold that shares and recommend

Wi-Fi Walkman: A wireless handhold that shares and recommend music on peer-to-peer networks Jun Wang, Marcel J.T. Reinders, Johan Pouwelse, Reginald L. Lagendijk

Faculty of EWI, Delft University of Technology,

Mekelweg 4, 2628 CD Delft, The Netherlands

________________________________________________________________________ The Wi-Fi walkman is a new application that investigates the technological and usability aspects of human-computer interaction with personalized, intelligent and context-aware wearable devices in ad-hoc wireless environments such as the future home, office, or university campuses. It is a small handheld device with a wireless link that contains music content. Users carry their own walkman around and listen to music. All this music content can be shared using ad-hoc networking. The walkman naturally interacts with the users and it is situated in peer-to-peer environments. Without annoying interactions, it can learn the users’ music interest/taste and consequently provide personalized music resources according to the current situated context and user’s interest.

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1. Introduction

Recently, with the rapid progress in information processing, communications, and storage technologies, the amount of information that we deal with in our daily lives has been rapidly increased and even more the types of information have been changed from homogeneous (textual) data only to heterogeneous data (audio, video, image, etc). We enjoy the entertainment and convenience brought to us by a variety of sources coming from digital TV, mp3 player, digital still image/video camera, etc., but are hampered to access this data by its sheer amount.

Not only the types of the information changed, but also the way people consume information changed. Peer-to-peer and ad-hoc networks, as new network topology, become a new way for people to distribute, exchange, and consume resources from their local storage devices in many different locations, such as the future home, office, or university campuses. There are two significant advantages of peer-to-peer and ad-hoc networks: 1) the replicas of the content among peers increase the content availability, 2) for the exchange of information, no requirements of centralized storage and management from the third parties make these networks have very low costs. Recently, those attributes attract a large body of people in the internet domain. For instance, through the internet peer-to-peer networks, such as Freenet[3] and Gnutella[4], a large number of people gained access to each other’s shared files. Furthermore, we believe that, in the recent future, the wireless communication technology will make those peer-to-peer networks wireless and exist in any place, and at any time.

In ad-hoc network environments, the volume of information is increasing far more quickly than our ability to digest it. The traditional textual keywords-based information retrieval approaches [5,6,7,8] encounter three major problems. Firstly, the transition from textual data to heterogeneous data requires large amount of textual Meta data on the one

hand. It is practically intractable to ask people to provide content as well as associated Meta data at the same time. On the other hand, automatic content analysis on the non-textual data is far from being efficient to get the Meta data that we need. Secondly, keywords are not semantically expressive enough to enable a seamless search, i.e. people hardly issue a textual query when they can not exactly express what they are looking for. Thirdly, in mobile environments, the user interface is constrained and consequently does not permit complex interactions between users and their handheld/wearable devices. Automatically assisting the user to acquire information and/or services that fits his/her interests is a non-trivial problem. Unfortunately, today’s computers merely act as information provider. One of the solutions to close this information gap is to increase the ability of computers to interpret the user’s interests and select relevant information on the user’s behalf.

To this regard, the research on information filtering is aroused to filter out, refine and systematically represent the relevant information. One of the solutions for overcoming the information overload is to provide personalized suggestions based on a history of a user’s likes and dislikes.

The Wi-Fi walkman is a case study that investigates the technological and usability aspects of human-computer interaction with personalized, intelligent and context-aware wearable devices in ad-hoc wireless environments such as the future home, office, or university campuses. It is a small handheld device with a wireless link that contains music content about the environment or from the user. Users carry their own walkman around and can both listen and record music content. All this music content can be shared using mobile ad-hoc networking. The walkman is situated in a peer-to-peer environment and naturally interacts with the users. Without annoying interactions with users, it can learn the users’ music taste and consequently provide personalized music resources to fit the user’s interest according to the user’s current situated context.

2. Related Work

Internet based peer-to-peer networks increase rapidly and it has given a large number of people the possibility of sharing resources in their local storage devices [1,2]. Recently, sharing resources in wireless networks has received some attention. In [2], the TunA system allows users to “tune in” to other nearby TunA music players and listen to what someone else is listening to. Another system, SoundPryer [1] allows drivers to jointly listen to music shared between cars on the road. Interestingly, these two applications show that the upcoming technologies start to take care about their social impact on everyday life, i.e. they bring people together that have been socially separated by the technologies for the last decades (such as TV, Internet, portable music player, etc.) Clearly, those technologies [1,2,3,4] are different from the traditional technologies in that they encourage people to make social interactions such as sharing and exchanging information. However, those applications are implemented far away from being called intelligent devices which aims to provide personalized services on user’s behalf. Differently, we present here a system which has the ability to steer the user’s interests/tastes and select/represent relevant information on the user’s behalf.

One of the most promising widely implemented and familiar technologies to understand user’s interest is collaborative filtering [9, 10, 11, 12]. Collaborative filtering based approaches utilize the correlations (commonalities) between users on the basis of their

ratings to predict and recommend items which have the highest correlations to the user’s rated /purchased items (user’s interest). Here, we will show how to use collaborative filtering to create a personalized music delivery system in a peer-to-peer environment.

3. Wi-Fi Walkman

The prototype of the Wi-Fi walkman on a Sharp Zaurus PDA is shown in Figure 1.

Fig. 1 The Wi-Fi walkman prototype on a Sharp Zaurus PDA

The Wi-Fi walkman allows to exchange music files (MP3 formatted) in a mobile network in a personalized way. The music files are stored on a local storage device (e.g. hard disk, fresh memory) of each Wi-Fi walkman and can be accessed through the Wi-Fi mobile network. The key issue in the Wi-Fi walkman is how to locate music files that the user will be interested in. To this regard, music recommendation is implemented as a user oriented music file filter to help the user to find relevant or desired music files according to current situated context and learned user interest.

3.1 Definition

In this section, we will define our research problems. Consider the case that users share music content in a peer-to-peer network. Each peer represents a Wi-Fi walkman used by a particular user.

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